The robotics and cognitive automation conundrum: Big bang deployment or small steps?


Posted by Peter Lowes and Anthony Abbattista on October 5, 2017

The old adage, “if it weren’t for the last minute, nothing would get done” may be a reality for organizations that wait too long to develop robotics and cognitive automation (R&CA) capabilities. Momentum is building as more companies use R&CA technologies to replicate human actions and judgment, thereby performing a wide and growing array of routine tasks. Should your organization get started today or wait for technologies to mature before making a major transformation?

Continue reading “The robotics and cognitive automation conundrum: Big bang deployment or small steps?”

Who determines ethics in a machine-run world?

A case for “Society in the loop artificial intelligence”


Posted by Jim Guszcza on May 19, 2017

As automation and robotics fueled by artificial intelligence (AI) become more mainstream, many areas of industry are set to undergo revolutionary changes. New sorts of jobs will likely emerge, some existing jobs will likely undergo transformation, and others may go away. There is good reason for concern about societal disruption, and a pressing need for enlightened societal-level dialogue. But we should not lose sight of the bright side to the creation of machines capable of helping with laborious “spade work.” AI has the potential to create significant value by making us more efficient, extending our intelligence and decision-making capabilities, saving organizations money, and generally helping societies run more smoothly.

Continue reading “Who determines ethics in a machine-run world?”

In financial services, data science may be a promising investment


Posted by John Houston on May 12, 2017

In the financial services arena, data scientists are taking a seat next to traditional business analysts, tasked with finding value in an ever-expanding quantity of data. By delivering smarter insights using analytics and cognitive technologies, data scientists help address problems in investing and trading strategies, portfolio management, regulatory reporting, client service, and more.

Continue reading “In financial services, data science may be a promising investment”

Beyond AI: Machine intelligence ushers in a new value-creation era


Posted by Nitin Mittal on March 16, 2017

Artificial intelligence (AI) may be in the headlines today, but machine intelligence is the future of advanced analytics. Machine intelligence is the collective term for cognitive computing capabilities that create value by augmenting employee performance, automating complex workloads, and developing human-like “cognitive agents.” Machine intelligence should be on your radar, because your competitors are probably all over it.

Continue reading “Beyond AI: Machine intelligence ushers in a new value-creation era”

Four things robots can do for your distribution center


Posted by Brenna Sniderman on December 09, 2016.

As we think about advanced, smart technologies, the thing that comes to mind is: robots. Well, maybe just for me. But I think of smart robots that can learn from their surroundings, adjust and figure things out on their own. Robots that can learn from each other, move objects, and work relatively more safely alongside humans, each augmenting the other.

Continue reading “Four things robots can do for your distribution center”

Moving to a precision medicine model in pharma


Posted by Nitin Mittal on October 10, 2016

Pharmaceutical companies have operated the same way for decades. Conduct R&D, run clinical trials, endure the regulatory gauntlet, and swing for a home run. This blockbuster-driven business model has produced miracle drugs and flops, winners and losers. And now, it’s going away.

Instead of investing in drugs whose success hinges on risky bets with their inevitable boom or bust cycles, pharma companies are pivoting to a precision medicine-based model–developing drugs to impact a specific patient’s malady or condition.

Continue reading “Moving to a precision medicine model in pharma”